The ever expanding and large complex array of scientific and engineering problems, requiring a more precise and responsive method for dynamical control and analysis, has defined the requirements for a better method of feedback and control, namely, by processing quadratic variables within the control loops of a new form of micro-computer-driven controller.
The background for such methodology lies in the network and system theories developed by Gabriel Kron whose tensor theory (a generalization of complex number theory), employing mathematical models of circuit networks, provided a ready solution of problems of great variety and immense complexity with the aid of electronic digital computers. These concepts form a part of modern combinatorial topology. However the theories of topological structure, in further development by mathematicians, have nearly lost all traces of their electrical origin and have been disassociated from the original network structure methodology.
In general, major progress in developing better mathematical and/or computer models has led to new theorems and computer algorithms that deal with problems involving variables about curves in a three or more (n) dimensional space. There are two corresponding methods recognized for explaining or mathematically modeling natural and synthesized phenomena extensively. One dealing with continuous variables is called tensor theory or point-set topology. The other dealing with discrete quantities is called combinatorial or algebraic topology. Point set topology underlies calculus, function theory, differential equations, and other methods of dealing with the properties of points infinitesimally distant from one another on curves or along straight lines. Under algebraic topology are included the theory of groups and networks, and other common methods of dealing with distinct entities. The former is especially adapted to deal with problems in high resolution and complex areas, the latter dealing with problems in large, time sensitive areas. However, there is no sharp line separating the two methods, since each overlaps the other, and the same mathematical algorithms available are common to both.
The quad linear motor (QLM), embodied in my U.S. Pat. No. 4,616,153, is a device embodied as a sub-system of a larger system. It is a generalized operational assembly of interconnecting but separable and dependent component parts. Functionally, it is designed as a system to provide linear-squared motion, i.e., both linear function and direction with time, position, direction, velocity and force as variables of motion equations having input constants set to control one or more of the above variables as an output control function, from a micro-computer system, to the motor armature.
The quad-linear motion of the system is a function of point-set topology or tensor calculus applied to a control and feedback scheme, this providing a powerful integration of mathematical models into the control system and expanded degree of accuracy and compound flexibility.
The quad-linear motor and its system is a statement of operational process functions of the parts, both collectively and independently, and including that which is operated on, generally called the input, to produce something generally called the output. The system function is a device procedure or scheme behaving according to computer driven algorithms, fitted to a defined function and operating on information (stored data), inputs and a time reference to yield motion and statistics, as a function of time and input data, as its output.
The system set forth herein is an integrated approach to the synthesis of an entire group of components as an entity, rather than simply as an assembly of individual and independent parts, i.e., a system in which each component is designed to interface properly with other components and a control computer, rather than to function independently. This defines a motor of unique design which cannot operate outside of, or independently of, its control system. However, such an integrated approach provides a linear motor with great flexibility and a high degree of both motion and functional linearity to perform various linear motion related tasks in what is designed to be a most efficient, accurate and adaptive method for producing complex linear motion functions as required in sensitive instruments, optics, lasers, guidance, robotic and medical perfusion technologies.
The QLM is embodied as a dynamical hybrid analog/digital computer system. This adaptive control system exhibits a crude form of learning in its self-adjustment toward an established goal. The hybrid arrangement is indispensable because one of the major problems in using a digital computer in a real-time continuous-data control system, is the time factor for encoding and decoding analog signal paths. The analog computer is also the ideal medium to execute combinatorial quadratic and linear equations in a parallel-processing mode. The digital computer will handle the point-set topology and the linear setpoints of the system.
In this microcomputer-based device, the analog computation follows high frequency variations, while the digital computation periodically corrects for low frequency drift, adjusting feedback parameters in the high frequency loops and establishing the proportional, integral and derivative setpoints of the analog-loop control computer. In the adaptive control sequence the digital computer reiteratively solves multiple-order polynomial, simultaneous and quadratic equations of mathematical process models, as in a nonlinear feedback loop. The ability to customize and optimize these mathematical models or algorithms is paramount to the adaptive control sequence.
The inventor is unaware of prior art having particular pertinence hereto, other than his above-referenced U.S. Pat. No. 4,616,153.